AIMC Topic: Neoplasm Staging

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Automated tumour budding quantification by machine learning augments TNM staging in muscle-invasive bladder cancer prognosis.

Scientific reports Mar 26, 2019
Tumour budding has been described as an independent prognostic feature in several tumour types. We report for the first time the relationship between tumour budding and survival evaluated in patients with muscle invasive bladder cancer. A machine lea...
Decision Trees Neoplasm Staging Survival Analysis Automation Proportional Hazards Models Kaplan-Meier Estimate Male Middle Aged Cohort Studies Image Processing, Computer-Assisted Urinary Bladder Neoplasms Muscles Humans Machine Learning Prognosis Female Aged Aged, 80 and over Adult
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Can We Accurately Identify Peritoneal Metastases Based on Their Appearance? An Assessment of the Current Practice of Intraoperative Gastrointestinal Cancer Staging.

Annals of surgical oncology Mar 25, 2019
BACKGROUND: Peritoneal lesions are common findings during operative abdominal cancer staging. The decision to perform biopsy is made subjectively by the surgeon, a practice the authors hypothesized to be imprecise. This study aimed to describe optica...
Aged Aged, 80 and over Adult Male Middle Aged Cohort Studies Humans Machine Learning Prognosis Female Gastrointestinal Neoplasms Image Processing, Computer-Assisted Peritoneal Neoplasms Adenocarcinoma Practice Patterns, Physicians' Follow-Up Studies Intraoperative Care Neoplasm Staging Laparoscopy
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Early experience with Watson for oncology in Korean patients with colorectal cancer.

PloS one Mar 25, 2019
BACKGROUND: Watson for oncology (WFO) is a cognitive computing system providing decision support. We evaluated the concordance rates between the treatment options determined by WFO and those determined by a multidisciplinary team (MDT).
Adult Patient Care Team Colorectal Neoplasms Interdisciplinary Communication Male Republic of Korea Middle Aged Female Humans User-Computer Interface Reproducibility of Results Software Decision Support Systems, Clinical Aged Algorithms Treatment Outcome Aged, 80 and over Computers Neoplasm Staging Retrospective Studies Expert Systems Medical Oncology Practice Guidelines as Topic
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Prediction of molecular subtypes of breast cancer using BI-RADS features based on a "white box" machine learning approach in a multi-modal imaging setting.

European journal of radiology Mar 21, 2019
PURPOSE: To develop and validate an interpretable and repeatable machine learning model approach to predict molecular subtypes of breast cancer from clinical metainformation together with mammography and MRI images.
Gene Expression Regulation, Neoplastic Multimodal Imaging Predictive Value of Tests Neoplasm Staging Retrospective Studies Female Adult Breast Neoplasms Middle Aged Humans Machine Learning
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Convolutional neural network to predict the local recurrence of giant cell tumor of bone after curettage based on pre-surgery magnetic resonance images.

European radiology Mar 11, 2019
OBJECTIVE: To predict the local recurrence of giant cell bone tumors (GCTB) on MR features and the clinical characteristics after curettage using a deep convolutional neural network (CNN).
Bone and Bones Giant Cell Tumor of Bone Curettage Bone Neoplasms Neoplasm Staging Neoplasm Recurrence, Local Image Interpretation, Computer-Assisted Preoperative Period Algorithms Prognosis Humans Female Male Neural Networks, Computer Young Adult Middle Aged Adult Adolescent Logistic Models Follow-Up Studies Magnetic Resonance Imaging
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Computer aided quantification of intratumoral stroma yields an independent prognosticator in rectal cancer.

Cellular oncology (Dordrecht, Netherlands) Mar 1, 2019
PURPOSE: Tumor-stroma ratio (TSR) serves as an independent prognostic factor in colorectal cancer and other solid malignancies. The recent introduction of digital pathology in routine tissue diagnostics holds opportunities for automated TSR analysis....
Humans Prognosis Female Neoplasm Staging Aged Rectal Neoplasms Male Stromal Cells Middle Aged Multivariate Analysis Diagnosis, Computer-Assisted Kaplan-Meier Estimate Deep Learning Pathology, Clinical
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ECM-CSD: An Efficient Classification Model for Cancer Stage Diagnosis in CT Lung Images Using FCM and SVM Techniques.

Journal of medical systems Feb 12, 2019
As is eminent, lung cancer is one of the death frightening syndromes among people in present cases. The earlier diagnosis and treatment of lung cancer can increase the endurance rate of the affected people. But, the structure of the cancer cell makes...
Neoplasm Staging Sensitivity and Specificity Humans Radiographic Image Interpretation, Computer-Assisted Algorithms Image Processing, Computer-Assisted Tomography, X-Ray Computed Lung Neoplasms Support Vector Machine Fuzzy Logic
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An Intelligent Clinical Decision Support System for Preoperative Prediction of Lymph Node Metastasis in Gastric Cancer.

Journal of the American College of Radiology : JACR Feb 4, 2019
PURPOSE: The aim of this study was to develop and validate a computational clinical decision support system (DSS) on the basis of CT radiomics features for the prediction of lymph node (LN) metastasis in gastric cancer (GC) using machine learning-bas...
Retrospective Studies Clinical Decision-Making Female Aged Stomach Neoplasms Male Middle Aged ROC Curve Decision Support Systems, Clinical Lymph Nodes Lymphatic Metastasis Humans Machine Learning Databases, Factual Prognosis Preoperative Care Neoplasm Invasiveness Predictive Value of Tests Neoplasm Staging Gastrectomy Multidetector Computed Tomography
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Deep convolutional neural network for the diagnosis of thyroid nodules on ultrasound.

Head & neck Feb 4, 2019
BACKGROUND: We designed a deep convolutional neural network (CNN) to diagnose thyroid malignancy on ultrasound (US) and compared the diagnostic performance of CNN with that of experienced radiologists.
Neoplasm Staging Observer Variation Ultrasonography, Doppler Adult Thyroid Neoplasms Humans Sensitivity and Specificity Thyroid Nodule Neural Networks, Computer Male ROC Curve Databases, Factual Middle Aged Image Processing, Computer-Assisted Retrospective Studies Cohort Studies Neoplasm Invasiveness Female Area Under Curve
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Machine Learning to Predict Delays in Adjuvant Radiation following Surgery for Head and Neck Cancer.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery Jan 29, 2019
OBJECTIVE: To apply a novel methodology with machine learning (ML) to a large national cancer registry to help identify patients who are high risk for delayed adjuvant radiation.
Databases, Factual Female Carcinoma, Squamous Cell Aged Male Neoplasm Staging Middle Aged Humans Time-to-Treatment Cohort Studies Machine Learning Radiotherapy, Adjuvant United States Algorithms Socioeconomic Factors Head and Neck Neoplasms Predictive Value of Tests
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